@article {551,
	title = {Using fuzzy preference orderings in theta-dominance with application to health monitoring of Li-ion batteries},
	journal = {Journal of Multiple-Valued Logic and Soft Computing},
	year = {2017},
	author = {Echevarr{\'\i}a, Yuviny and Couso, In{\'e}s and Anse{\'a}n, David and Blanco, Cecilio and S{\'a}nchez, Luciano}
}
@conference {10.1007/978-3-319-32034-2_21,
	title = {Assessment of Multi-Objective Optimization Algorithms for Parametric Identification of a Li-Ion Battery Model},
	booktitle = {Hybrid Artificial Intelligent Systems},
	year = {2016},
	pages = {250{\textendash}260},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {The identification of intelligent models of Li-Ion batteries is a major issue in Electrical Vehicular Technology. On the one hand, the fitness of such models depends on the recursive evaluation of a set of nonlinear differential equations over a representative path in the state space, which is a time consuming task. On the other hand, battery models are intrinsically unstable, and small differences in the initial state or the system, as well as imprecisions in the parameter values, may trigger large differences in the output. Hence, learning battery models from data is a complex multi-modal problem and the parameters of these models must be determined with a high accuracy. In addition to this, producing a dynamical model of a battery is a multi-criteria problem, because the predictive capabilities of the model must be estimated in both the voltage and the temperature domains. In this paper, a selection of state-of-the-art Multi-Objective Optimization Algorithms (SPEA2, NSGA-II, OMOPSO, NSGA-III and MOEA/D) are assessed with regard to their suitability for identifying a model of a Li-Ion battery. The dominance relations that occur between the Pareto fronts are discussed in terms of binary additive {\$}{\$}{\backslash}epsilon {\$}{\$}ϵ-quality indicators. It is concluded that each of the standard implementations of these algorithms has different issues with this particular problem, MOEA/D and NSGA-III being the best overall alternatives.},
	isbn = {978-3-319-32034-2},
	author = {Echevarr{\'\i}a, Yuviny and S{\'a}nchez, Luciano and Blanco, Cecilio},
	editor = {Mart{\'\i}nez-{\'A}lvarez, Francisco and Troncoso, Alicia and Quinti{\'a}n, H{\'e}ctor and Corchado, Emilio}
}
@conference {10.1007/978-3-319-44636-3_29,
	title = {Genetic Fuzzy Modelling of Li-Ion Batteries Through a Combination of Theta-DEA and Knowledge-Based Preference Ordering},
	booktitle = {Advances in Artificial Intelligence},
	year = {2016},
	pages = {310{\textendash}320},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Learning semi-physical fuzzy models of rechargeable Li-Ion batteries from data involves solving a complex multicriteria optimization task where the accuracies of the approximations of the different observable variables are balanced. The fitness function of this problem depends on the recursive evaluation of a set of differential equations, where fuzzy rule-based systems are embedded as nonlinear blocks. Evaluating this function is a time consuming process, thus algorithms that efficiently promote diversity and hence demand a low number of evaluations of the fitness function are preferred. In this paper, a comparison is carried out between some recent genetic algorithms, whose performances are assessed in this particular modelling problem. It is concluded that the combination of the recent {\$}{\$}{\backslash}theta {\$}{\$}-Dominance Evolutionary Algorithm ({\$}{\$}{\backslash}theta {\$}{\$}-DEA) with a Knowledge-based precedence operator, that improves the selection, is a sensible choice. Dominance relations between the Pareto fronts are assessed in terms of binary additive {\$}{\$}{\backslash}epsilon {\$}{\$}-quality indicators.},
	isbn = {978-3-319-44636-3},
	author = {Echevarr{\'\i}a, Yuviny and S{\'a}nchez, Luciano and Blanco, Cecilio},
	editor = {Luaces , Oscar and G{\'a}mez, Jos{\'e} A. and Barrenechea, Edurne and Troncoso, Alicia and Galar, Mikel and Quinti{\'a}n, H{\'e}ctor and Corchado, Emilio}
}
@article {article,
	title = {Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster},
	journal = {Energies},
	volume = {9},
	year = {2016},
	month = {03},
	pages = {197},
	doi = {10.3390/en9030197},
	author = {Coca{\~n}a-Fern{\'a}ndez, Alberto and S{\'a}nchez, Luciano and Ranilla, Josr}
}
@conference {inproceedings,
	title = {RKEEL: Using KEEL in R code},
	year = {2016},
	month = {07},
	pages = {257-264},
	doi = {10.1109/FUZZ-IEEE.2016.7737695},
	author = {Moyano, Jose and S{\'a}nchez, Luciano}
}
@conference {10.1007/978-3-319-19719-7_23,
	title = {Energy-Efficient Sound Environment Classifier for Hearing Aids Based on Multi-objective Simulated Annealing Programming},
	booktitle = {10th International Conference on Soft Computing Models in Industrial and Environmental Applications},
	year = {2015},
	pages = {261{\textendash}270},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {A methodology for designing classifiers through multicriteria metaheuristics is introduced. The purpose of the new method is to jointly optimize the expected total classification cost and the energy consumption of the device the classifier is implemented on. A numerical study is provided, where different alternatives are implemented on a hearing aid. This aid is capable of automatically classifying the acoustic environment that surrounds the user and choosing the parameters of the amplification that are best adapted to the user{\textquoteright}s comfort. The proposed method attains relevant improvements in energy consumption with small to negligible loss in classification accuracy with respect to a selection of algorithms.},
	isbn = {978-3-319-19719-7},
	author = {Coca{\~n}a-Fern{\'a}ndez, Alberto and S{\'a}nchez, Luciano and Ranilla, Jos{\'e} and Gil-Pita, Roberto and Ayll{\'o}n, David},
	editor = {Herrero, {\'A}lvaro and Sedano, Javier and Baruque, Bruno and Quinti{\'a}n, H{\'e}ctor and Corchado, Emilio}
}
@conference {654,
	title = {Generalized stochastic orderings applied to the study of perfomance of  machine learning algorithm},
	booktitle = {The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT)},
	year = {2015},
	month = {06},
	address = {Gij{\'o}n, Asturias(Spain)},
	author = {Couso, In{\'e}s and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {Online SOC estimation of Li-FePO4 batteries through an observer of the system state with minimal nonspecificity},
	year = {2015},
	month = {08},
	pages = {1-8},
	doi = {10.1109/FUZZ-IEEE.2015.7337901},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s and Blanco, Cecilio}
}
@article {article,
	title = {An Equivalent Circuit Model With Variable Effective Capacity for LiFePO4 Batteries},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {63},
	year = {2014},
	month = {10},
	pages = {3592-3599},
	doi = {10.1109/TVT.2014.2309394},
	author = {Blanco, Cecilio and S{\'a}nchez, Luciano and Gonzalez, M and Ant{\'o}n, Juan Carlos and Garc{\'\i}a Fern{\'a}ndez, V{\'\i}ctor and Viera, Juan}
}
@article {article,
	title = {Cost-Sensitive Learning of Fuzzy Rules for Imbalanced Classification Problems Using FURIA},
	journal = {International Journal of Uncertainty Fuzziness and Knowledge-Based Systems},
	volume = {22},
	year = {2014},
	month = {10},
	pages = {643-675},
	doi = {10.1142/S0218488514500330},
	author = {Palacios, Ana and Trawinski, Krzysztof and O. Cord{\'o}n and S{\'a}nchez, Luciano}
}
@article {article,
	title = {Interval-valued Blind Source Separation Applied to AI-based Prognostic Fault Detection of Aircraft Engines},
	journal = {Journal of Multiple-Valued Logic and Soft Computing},
	volume = {22},
	year = {2014},
	month = {01},
	pages = {151-166},
	author = {Martinez, Alvaro and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {10.1007/978-3-319-07617-1_30,
	title = {Mutual Information-Based Feature Selection in Fuzzy Databases Applied to Searching for the Best Code Metrics in Automatic Grading},
	booktitle = {Hybrid Artificial Intelligence Systems},
	year = {2014},
	pages = {330{\textendash}341},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Massive open online courses have a large impact in developing countries, helping to improve education in poor regions. However, instructors cannot review open-ended work from students as they do in smaller class settings. In the context of computer science courses where students{\textquoteright} code is reviewed, there are some methods that use code metrics for automatically providing the student with a qualification. Notwithstanding this, a high number of incomplete and conflicting sources of information must be combined in the prediction process, and it may happen that there are too many variables involved to make any meaningful predictions. In this work a new method is proposed for sorting a set of metrics by their relevance in the prediction of student qualifications that can cope with incomplete and imprecise results. Measurements taken on variable-sized sets of assignments are aggregated into fuzzy values, and a fuzzy random variable-based definition of mutual information is used to build a partial ranking of metrics according to their predictive power. The most relevant metrics are fed to a genetic fuzzy system that models the dependence between the fuzzy code metrics and the qualifications of the corresponding students. A set comprising 800 source code files, collected in classroom Computer Science lectures taught between 2013 and 2014, was used for validating the hypotheses of this research, and it was found that the new ranking method significantly improves the predictive capability of the models.},
	isbn = {978-3-319-07617-1},
	author = {Otero, Jos{\'e} and Su{\'a}rez, Rosario and S{\'a}nchez, Luciano},
	editor = {Polycarpou, Marios and de Carvalho, Andr{\'e} C. P. L. F. and Pan, Jeng-Shyang and Wo{\'z}niak, Micha{\l} and Quinti{\'a}n, H{\'e}ctor and Corchado, Emilio}
}
@conference {10.1007/978-3-319-08644-6_31,
	title = {Selecting the Most Informative Inputs in Modelling Problems with Vague Data Applied to the Search of Informative Code Metrics for Continuous Assessment in Computer Science Online Courses},
	booktitle = {Rough Sets and Current Trends in Computing},
	year = {2014},
	pages = {299{\textendash}308},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {Sorting a set of inputs for relevance in modeling problems may be ambiguous if the data is vague. A general extension procedure is proposed in this paper that allows applying different deterministic or random feature selection algorithms to fuzzy data. This extension is based on a model of the relevance of a feature as a possibility distribution. The possibilistic relevances are ordered with the help of a fuzzy ranking. A practical problem where the most informative software metrics are searched for in an automatic grading problem is solved with this technique.},
	isbn = {978-3-319-08644-6},
	author = {Otero, Jos{\'e} and Del Rosario Su{\'a}rez, Maria and Palacios, Ana and Couso, In{\'e}s and S{\'a}nchez, Luciano},
	editor = {Cornelis, Chris and Kryszkiewicz, Marzena and {\'S}lȩzak, Dominik and Ruiz, Ernestina Menasalvas and Bello, Rafael and Shang, Lin}
}
@conference {inproceedings,
	title = {Supervising classrooms comprising children with dyslexia and other learning problems with graphical exploratory analysis for fuzzy data: Presentation of the software tool and case study},
	booktitle = {IEEE International Conference on Fuzzy Systems},
	year = {2014},
	month = {07},
	pages = {2133-2140},
	doi = {10.1109/FUZZ-IEEE.2014.6891710},
	author = {Palacios, Ana and S{\'a}nchez, Luciano}
}
@article {585,
	title = {A Genetic Fuzzy Linguistic Combination Method for Fuzzy Rule-based Multiclassifiers Revista: IEEE Transactions on Fuzzy Systems},
	journal = {IEEE Transactions on Fuzzy Systems},
	volume = {21},
	number = {5},
	year = {2013},
	month = {01},
	pages = {950-965},
	issn = {1063-6706},
	doi = {10.1109/TFUZZ.2012.2236844},
	author = {O. Cord{\'o}n and S{\'a}nchez, Luciano and Arnaud Quirin and Trawinski, Krzysztof}
}
@article {article,
	title = {A methodology for exploiting the tolerance for imprecision in genetic fuzzy systems and its application to characterization of rotorblade leading edge materials},
	journal = {Mechanical Systems and Signal Processing},
	volume = {37},
	year = {2013},
	month = {06},
	pages = {76-91},
	doi = {10.1016/j.ymssp.2012.02.009},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s and Palacios, Ana and Palacios, Jos{\'e}}
}
@article {doi:10.1142/S0218488512400156,
	title = {COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS},
	journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
	volume = {20},
	number = {supp02},
	year = {2012},
	pages = {51-71},
	abstract = {An extension of the Adaboost algorithm for obtaining fuzzy rule-based systems from low quality data is combined with preprocessing algorithms for equalizing imbalanced datasets. With the help of synthetic and real-world problems, it is shown that the performance of the Adaboost algorithm is degraded in presence of a moderate uncertainty in either the input or the output values. It is also established that a preprocessing stage improves the accuracy of the classifier in a wide range of binary classification problems, including those whose imbalance ratio is uncertain.},
	doi = {10.1142/S0218488512400156},
	url = {https://doi.org/10.1142/S0218488512400156},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Future Performance Modeling in Athletism with Low Quality Data-based Genetic Fuzzy Systems},
	journal = {Multiple-Valued Logic and Soft Computing},
	volume = {17},
	year = {2011},
	month = {01},
	pages = {207-228},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {Managing stochastic algorithms cross-validation variability using an interval valued multiple comparison procedure},
	booktitle = {International Conference on Intelligent Systems Design and Applications},
	year = {2011},
	month = {11},
	pages = {1391-1396},
	doi = {10.1109/ISDA.2011.6121854},
	author = {Otero, Jos{\'e} and S{\'a}nchez, Luciano and Palacios, Ana and Couso, In{\'e}s}
}
@article {article,
	title = {Obtaining fuzzy rules from interval-censored data with genetic algorithms and a random sets-based semantic of the linguistic labels},
	journal = {Soft Comput.},
	volume = {15},
	year = {2011},
	month = {10},
	pages = {1945-1957},
	doi = {10.1007/s00500-010-0627-6},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Singular spectral analysis of ill-known signals and its application to predictive maintenance of windmills with SCADA records},
	journal = {Soft Computing},
	volume = {16},
	year = {2011},
	month = {05},
	doi = {10.1007/s00500-011-0767-3},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {article,
	title = {A coevolutionary genetic algorithm able to learn a FRBS and detect the less informative instances in low quality problems},
	booktitle = {Congreso Espa{\~n}ol sobre tecnolog{\'\i}as y l{\'o}gica fuzzy},
	year = {2010},
	month = {01},
	address = {Huelva (Espa{\~n}a)},
	author = {S{\'a}nchez, Luciano}
}
@inbook {inbook,
	title = {Introduction to the Experimental Design in the Data Mining Tool KEEL},
	year = {2010},
	month = {01},
	pages = {1-25},
	isbn = {978-1-61520-757-2},
	author = {Alcala-Fdez, Jesus and Garcia, S and S{\'a}nchez, Luciano and Robles, I and M. J. del Jesus and Bernado-Mansilla, E and Peregrin, Antonio and F. Herrera}
}
@conference {inproceedings,
	title = {A Baseline Learning Genetic Fuzzy Classifier Based on Low Quality Data.},
	year = {2009},
	month = {01},
	pages = {803-808},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {10.1007/978-3-642-02319-4_79,
	title = {A Minimum-Risk Genetic Fuzzy Classifier Based on Low Quality Data},
	booktitle = {Hybrid Artificial Intelligence Systems},
	year = {2009},
	pages = {654{\textendash}661},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {Minimum risk classification problems use a matrix of weights for defining the cost of misclassifying an object. In this paper we extend a simple genetic fuzzy system (GFS) to this case. In addition, our method is able to learn minimum risk fuzzy rules from low quality data. We include a comprehensive description of the new algorithm and discuss some issues about its fuzzy-valued fitness function. A synthetic problem, plus two real-world datasets, are used to evaluate our proposal.},
	isbn = {978-3-642-02319-4},
	author = {Palacios, Ana M. and S{\'a}nchez, Luciano and Couso, In{\'e}s},
	editor = {Corchado, Emilio and Wu, Xindong and Oja, Erkki and Herrero, {\'A}lvaro and Baruque, Bruno}
}
@article {article,
	title = {Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets},
	journal = {Evolutionary Intelligence},
	volume = {2},
	year = {2009},
	month = {11},
	pages = {73-84},
	doi = {10.1007/s12065-009-0024-1},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@conference {inproceedings,
	title = {GFS-Based Analysis of Vague Databases in High Performance Athletics},
	year = {2009},
	month = {09},
	pages = {602-609},
	doi = {10.1007/978-3-642-04394-9_73},
	author = {Palacios, Ana and Couso, In{\'e}s and S{\'a}nchez, Luciano}
}
@article {article,
	title = {Obtaining linguistic fuzzy rule-based regression models from imprecise data with multiobjective genetic algorithms},
	journal = {Soft Comput.},
	volume = {13},
	year = {2009},
	month = {03},
	pages = {467-479},
	doi = {10.1007/s00500-008-0362-4},
	author = {S{\'a}nchez, Luciano and Otero, Jos{\'e} and Couso, In{\'e}s}
}
@article {Villar2009,
	title = {Taximeter verification with GPS and soft computing techniques},
	journal = {Soft Computing},
	volume = {14},
	number = {4},
	year = {2009},
	month = {Mar},
	pages = {405},
	abstract = {Until recently, local governments in Spain were using machines with rolling cylinders for verifying taximeters. However, the condition of the tires can lead to errors in the process and the mechanical construction of the test equipment is not compatible with certain vehicles. Thus, a new measurement device needs to be designed. In our opinion, the verification of a taximeter will not be reliable unless measurements taken on an actual taxi run are used. GPS sensors are intuitively well suited for this process, because they provide the position and the speed with independence of those car devices that are under test. But there are legal problems that make difficult the use of GPS-based sensors: GPS coordinate measurements do not match exactly real coordinates and, generally speaking, we are not given absolute tolerances. We can not know whether the maximum error is always lower than, for example, 7~m. However, we might know that 50{\%} of the measurements lie on a circle with a radius of 7~m, centered on the real position. In this paper we describe a practical application where these legal problems have been solved with soft computing based technologies. In particular, we propose to characterize the uncertainty in the GPS with fuzzy techniques, so that we can reuse certain recent algorithms, formerly intended for being used in genetic fuzzy systems, to this new context. Specifically, we propose a new method for computing an upper bound of the length of the trajectory, taking into account the vagueness of the GPS data. This bound will be computed using a modified multiobjective evolutionary algorithm, which can optimize a fuzzy valued function. The accuracy of the measurements will be improved further by combining it with restrictions based on the dynamic behavior of the vehicles.},
	issn = {1433-7479},
	doi = {10.1007/s00500-009-0414-4},
	url = {https://doi.org/10.1007/s00500-009-0414-4},
	author = {Villar, Jos{\'e} and Otero, Adolfo and Otero, Jos{\'e} and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {A Minimum Risk Wrapper Algorithm for Genetically Selecting Imprecisely Observed Features, Applied to the Early Diagnosis of Dyslexia},
	booktitle = {Lecture Notes in Computer Science - LNCS},
	volume = {5271},
	year = {2008},
	month = {09},
	pages = {608-615},
	doi = {10.1007/978-3-540-87656-4_75},
	author = {S{\'a}nchez, Luciano and Palacios, Ana and Couso, In{\'e}s}
}
@conference {10.1007/978-3-540-85027-4_16,
	title = {Defuzzification of Fuzzy p-Values},
	booktitle = {Soft Methods for Handling Variability and Imprecision},
	year = {2008},
	pages = {126{\textendash}132},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {We provide a new description of the notion of fuzzy p-value, within the context of the theory of imprecise probabilities. The fuzzy p-value is viewed as a representation of a certain second-order possibility measure. According to Walley, any second-order possibility measure can be converted into a pair of lower and upper probabilities. Thus, we can convert the fuzzy p-value into an interval in the real line. We derive a construction of imprecise (but non fuzzy) tests, which are formally similar to recent tests used to manage with set-valued data.},
	isbn = {978-3-540-85027-4},
	author = {Couso, In{\'e}s and S{\'a}nchez, Luciano},
	editor = {Dubois, Didier and Lubiano, M. Asunci{\'o}n and Prade, Henri and Gil, Mar{\'\i}a {\'A}ngeles and Grzegorzewski, Przemys{\l}aw and Hryniewicz, Olgierd}
}
@article {article,
	title = {Disenos experimentales y tests estadisticos, tendencias actuales en Machine Learning.},
	year = {2007},
	month = {01},
	author = {Otero, J and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {Selecting an Appropriate Statistical Test for Comparing Multiple Experiments in Evolutionary Machine Learning},
	year = {2007},
	month = {09},
	author = {Otero, Jos{\'e} and S{\'a}nchez, Luciano and Alcala-Fdez, Jesus}
}
@conference {article,
	title = {Boosting of fuzzy models for high-dimensional imprecise datasets},
	booktitle = {Information Processing and Management of Uncertainty in Knowledge-Based Systems},
	year = {2006},
	month = {07},
	address = {Par{\'\i}s (Francia)},
	author = {S{\'a}nchez, Luciano and Ram{\'o}n, Jos{\'e}}
}
@conference {Villar:2006:GAE:2176301.2176330,
	title = {Genetic Algorithms for Estimating Longest Path from Inherently Fuzzy Data Acquired with GPS},
	booktitle = {Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning},
	series = {IDEAL{\textquoteright}06},
	year = {2006},
	pages = {232{\textendash}240},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = {Berlin, Heidelberg},
	isbn = {3-540-45485-3, 978-3-540-45485-4},
	doi = {10.1007/11875581_28},
	url = {http://dx.doi.org/10.1007/11875581_28},
	author = {Villar, Jos{\'e} and Otero, Adolfo and Otero, Jos{\'e} and S{\'a}nchez, Luciano}
}
@article {Otero2006,
	title = {Induction of descriptive fuzzy classifiers with the Logitboost algorithm},
	journal = {Soft Computing},
	volume = {10},
	number = {9},
	year = {2006},
	month = {Jul},
	pages = {825{\textendash}835},
	abstract = {Recently, Adaboost has been compared to greedy backfitting of extended additive models in logistic regression problems, or {\textquoteleft}{\textquoteleft}Logitboost{\textquoteleft}{\textquoteleft}. The Adaboost algorithm has been applied to learn fuzzy rules in classification problems, and other backfitting algorithms to learn fuzzy rules in modeling problems but, up to our knowledge, there are not previous works that extend the Logitboost algorithm to learn fuzzy rules in classification problems.},
	issn = {1433-7479},
	doi = {10.1007/s00500-005-0011-0},
	url = {https://doi.org/10.1007/s00500-005-0011-0},
	author = {Otero, Jos{\'e} and S{\'a}nchez, Luciano}
}
@conference {article,
	title = {A fuzzy definition of mutual information with application to the design of genetic fuzzy classifiers},
	booktitle = {International Conference on Machine Intelligencea: ACIDCA-ICMI },
	year = {2005},
	month = {01},
	address = {Tunez},
	author = {S{\'a}nchez, Luciano and Su{\'a}rez, Mar{\'\i}a and Couso, In{\'e}s}
}
@article {article,
	title = {Assessing the differences in accuracy between GFSs with bootstrap tests},
	year = {2005},
	month = {01},
	author = {S{\'a}nchez, Luciano and Alcala-Fdez, Jesus}
}
@conference {article,
	title = {Managing imprecisely observed data in Genetic Fuzzy Models by means of a fuzzy-valued fitness function},
	booktitle = {Congreso espa{\~n}ol de metaheur{\'\i}sticas, algoritmos evolutivos y bioinspirados.},
	year = {2005},
	month = {01},
	address = {Granada (Espa{\~n}a)},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {A fast genetic method for inducting descriptive fuzzy models},
	journal = {Fuzzy Sets and Systems},
	volume = {141},
	year = {2004},
	month = {01},
	pages = {33-46},
	doi = {10.1016/S0165-0114(03)00112-X},
	author = {S{\'a}nchez, Luciano and Otero, Jos{\'e}}
}
@conference {article,
	title = {Algoritmo GA-P Difuso para la Generaci{\'o}n de Controladores en Edificios Inteligentes},
	booktitle = {Congreso espa{\~n}ol de metaheur{\'\i}sticas, algoritmos evolutivos y bioinspirados.},
	year = {2004},
	month = {01},
	address = {C{\'o}rdoba (Espa{\~n}a)},
	author = {Lopez, Antonio and Doctor, Faiyaz and S{\'a}nchez, Luciano}
}
@conference {article,
	title = {Preliminary results on the application of boosting to learn weighted fuzzy rules under single-winner inference},
	booktitle = {Congreso espa{\~n}ol de metaheur{\'\i}sticas, algoritmos evolutivos y bioinspirados.},
	year = {2004},
	address = {C{\'o}rdoba-Espa{\~n}a},
	author = {S{\'a}nchez, Luciano and Otero, Jos{\'e} and Su{\'a}rez, Mar{\'\i}a}
}
@inbook {inbook,
	title = {Proyecto KEEL: Desarrollo de una herramienta para el an{\'a}lisis e implementaci{\'o}n de algoritmos de extracci{\'o}n de conocimiento evolutivos},
	year = {2004},
	month = {01},
	pages = {413-424},
	isbn = {84-688-8442-1},
	author = {Alcala-Fdez, Jesus and M. J. del Jesus and Garrell, Josep-Maria and F. Herrera and Mart{\'\i}nez, Cesar and S{\'a}nchez, Luciano}
}
@article {article,
	title = {Supply Estimation Using Coevolutionary Genetic Algorithms in the Spanish Electrical Market},
	journal = {Applied Intelligence},
	volume = {21},
	year = {2004},
	month = {07},
	pages = {7-24},
	doi = {10.1023/B:APIN.0000027764.76082.00},
	author = {Mar{\'\i}n, Enrique and S{\'a}nchez, Luciano}
}
@inbook {697,
	title = {Un estudio emp{\'\i}rico preliminar sobre los tests estad{\'\i}sticos m{\'a}s habituales en el aprendizaje autom{\'a}tico},
	booktitle = {Tendencias de la miner{\'\i}a de datos en Espa{\~n}a},
	number = {403-412},
	year = {2004},
	publisher = {R. Gir{\'a}ldez, J.C. Riquelme, J.S. Aguilar},
	organization = {R. Gir{\'a}ldez, J.C. Riquelme, J.S. Aguilar},
	address = {Santander (Espa{\~n}a)},
	issn = {84-688-8442-1},
	author = {F. Herrera and Hervas-Mart{\'\i}nez, Cesar and Otero, J and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {Genetic Search of Block-Based Structures of Dynamical Process Models},
	volume = {2686},
	year = {2003},
	month = {06},
	pages = {526-533},
	doi = {10.1007/3-540-44868-3_67},
	author = {Lopez, Antonio and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {Optimizing Supply Strategies in the Spanish Electrical Market.},
	volume = {2687},
	year = {2003},
	month = {06},
	pages = {353-360},
	doi = {10.1007/3-540-44869-1_45},
	author = {Mar{\'\i}n, Enrique and S{\'a}nchez, Luciano}
}
@inbook {S{\'a}nchez2003,
	title = {Tuning fuzzy partitions or assigning weights to fuzzy rules: which is better?},
	booktitle = {Accuracy Improvements in Linguistic Fuzzy Modeling},
	year = {2003},
	pages = {366{\textendash}385},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {The accuracy of linguistic classifiers can be improved with several techniques, but they all compromise the interpretability of the rule base up to a certain degree. Assigning weights to fuzzy rules and tuning the memberships associated to linguistic variables are two of the most common methods. In this work we study whether tuning the membership functions in a linguistic classifier is better or not than adjusting rule weights, in terms of the interpretability of the rule base and the complexity of the output.},
	isbn = {978-3-540-37058-1},
	doi = {10.1007/978-3-540-37058-1_15},
	url = {https://doi.org/10.1007/978-3-540-37058-1_15},
	author = {S{\'a}nchez, Luciano and Otero, Jos{\'e}},
	editor = {Casillas, Jorge and O. Cord{\'o}n and F. Herrera and Magdalena, Luis}
}
@conference {737,
	title = {Aprendizaje jer{\'a}rquico por refuerzo mediante programaci{\'o}n gen{\'e}tica dirigida por gram{\'a}ticas},
	booktitle = {Congreso Espa{\~n}ol de algoritmos evolutivos y bioinspirados AEB-02},
	year = {2002},
	month = {01},
	address = {M{\'e}rida (Espa{\~n}a)},
	author = {Carbajal, Santiago and S{\'a}nchez, Luciano}
}
@conference {738,
	title = {Optimizaci{\'o}n gen{\'e}tico borrosa de par{\'a}metros en un sistema de bajo coste para la medici{\'o}n visual de cotas de veh{\'\i}culos},
	booktitle = {Congreso Espa{\~n}ol sobre tecnolog{\'\i}as y l{\'o}gica fuzzy},
	year = {2002},
	month = {01},
	address = {Le{\'o}n (Espa{\~n}a)},
	author = {Otero, Jos{\'e} and Otero, Adolfo and Junco, Luis and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {Graph Based GP Applied to Dynamical Systems Modeling},
	volume = {2084},
	year = {2001},
	month = {06},
	pages = {725-732},
	doi = {10.1007/3-540-45720-8_87},
	author = {Lopez, Antonio and L{\'o}pez Garc{\'\i}a, Hilario and S{\'a}nchez, Luciano}
}
@conference {717,
	title = {Approximating The Discrete Space Equation From Chaotic Noisy Data},
	booktitle = {International Conference On Information Processing and Management Of Uncertainty In Knowledge-Based System},
	year = {2000},
	month = {01},
	url = {http://di002.edv.uniovi.es/~luciano/documentos/c25.pdf},
	author = {Fern{\'a}ndez, A. and S{\'a}nchez, Luciano and Navarro, J.J.}
}
@inbook {inbook,
	title = {GA-P based Feature Selection and Classification combining different Methods of Texture Analysis},
	year = {2000},
	month = {09},
	pages = {209-219},
	isbn = {978-981-02-4364-7},
	doi = {10.1142/9789812792563_0017},
	author = {Cano, Fernando and Junco, Luis and S{\'a}nchez, Luciano}
}
@article {article,
	title = {Niching scheme for steady state GA-P and its application to fuzzy rule based classifiers induction},
	year = {2000},
	month = {01},
	author = {S{\'a}nchez, Luciano and Antonio Corrales Gonz{\'a}lez, Jos{\'e}}
}
@conference {729,
	title = {Using the adabooth algorithm to induce fuzzy rules in classification problems},
	booktitle = {X Congreso Espa{\~n}ol sobre Tecnolog{\'\i}as y L{\'o}gica Difusa},
	year = {2000},
	month = {09},
	address = {Santander (Espa{\~n}a)},
	author = {Junco, Luis and S{\'a}nchez, Luciano}
}
@conference {inproceedings,
	title = {Evolving Fuzzy Rule Based Classifiers with GA-P: A Grammatical Approach},
	volume = {1598},
	year = {1999},
	month = {05},
	pages = {203-210},
	doi = {10.1007/3-540-48885-5_17},
	author = {Carbajal, Santiago and Gonz{\'a}lez Martinez, Ferm{\'\i}n and S{\'a}nchez, Luciano}
}
@article {Cord{\'o}n1999,
	title = {Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques},
	journal = {Applied Intelligence},
	volume = {10},
	number = {1},
	year = {1999},
	month = {Jan},
	pages = {5{\textendash}24},
	abstract = {Real-world electrical engineering problems can take advantage of the last Data Analysis methodologies. In this paper we will show that Genetic Fuzzy Rule-Based Systems and Genetic Programming techniques are good choices for tackling with some practical modeling problems. We claim that both evolutionary processes may produce good numerical results while providing us with a model that can be interpreted by a human being. We will analyze in detail the characteristics of these two methods and we will compare them to the some of the most popular classical statistical modeling methods and neural networks.},
	issn = {1573-7497},
	doi = {10.1023/A:1008384630089},
	url = {https://doi.org/10.1023/A:1008384630089},
	author = {O. Cord{\'o}n and F. Herrera and S{\'a}nchez, Luciano}
}
@conference {10.1007/3-540-64582-9_778,
	title = {Computing the spanish medium electrical line maintenance costs by means of evolution-based learning processes},
	booktitle = {Methodology and Tools in Knowledge-Based Systems},
	year = {1998},
	pages = {478{\textendash}486},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {In this paper, we deal with the problem of computing the maintenance costs of electrical medium line in spanish towns. To do so, we present two Data Analysis tools taking as a base Evolutionary Algorithms, the Interval Genetic Algorithm-Programming method to perform symbolic regression and Genetic Fuzzy Rule-Based Systems to design fuzzy models, and use them to solve the said problem. Results obtained are compared with other kind of techniques: classical regression and neural modeling.},
	isbn = {978-3-540-69348-2},
	author = {O. Cord{\'o}n and F. Herrera and S{\'a}nchez, Luciano},
	editor = {Mira, Jos{\'e} and del Pobil, Angel Pasqual and Ali, Moonis}
}
@conference {711,
	title = {Estimaci{\'o}n de la Longitud de L{\'\i}nea de Baja Tensi{\'o}n Mediante T{\'e}cnicas Evolutivas de An{\'a}lisis de Datos},
	booktitle = {8{\textordfeminine} Reuni{\'o}n Nacional de Grupos de Investigaci{\'o}n en Ingenier{\'\i}a El{\'e}ctrica},
	year = {1998},
	author = {O. Cord{\'o}n and Sp{\'\i}n, Antonio and Fajardo, Waldo and F. Herrera and S{\'a}nchez, Luciano}
}
@article {article,
	title = {Learning from imprecise examples with GA-P algorithms},
	journal = {Mathware \& soft computing, ISSN 1134-5632, Vol. 5, N{\textordmasculine}. 2-3, 1998, pags. 305-319},
	volume = {5},
	year = {1998},
	month = {01},
	author = {S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
@article {article,
	title = {Localization and fuzzy classification of manufacturing defects in sheets of glass},
	volume = {5},
	year = {1998},
	month = {01},
	author = {Junco, Luis and S{\'a}nchez, Luciano}
}
@conference {10.1007/3-540-60406-5_7,
	title = {Using a symbolic model checker for verify safety properties in SA/RT models},
	booktitle = {Software Engineering {\textendash}- ESEC {\textquoteright}95},
	year = {1995},
	pages = {59{\textendash}75},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	address = {Berlin, Heidelberg},
	abstract = {In this paper, structured methods are integrated with formal verification methods based on temporal logic. The goal is to use an operational method (SA/RT) for the system behavioural specification, and to complement this with safety properties expressed in a declarative style using temporal logic (CTL). These properties are checked against the operational specification using a model checker (SMV).},
	isbn = {978-3-540-45552-3},
	author = {Tuya, Javier and S{\'a}nchez, Luciano and Corrales, Jose A.},
	editor = {Sch{\"a}fer, Wilhelm and Botella, Pere}
}
